The first satellite constellation emitting positioning signals was put in place for military applications by the American state (global positioning system or GPS) from the start of the eighties. Since then, GPS signals have been used by professional civil applications (management of fleets of trucks, aerial navigation aids, geodetic surveys, etc.) and more recently in mass-market applications (automotive navigation with on-board terminals and pedestrian navigation with smartphone type terminals). Other constellations have been put in place by the Russian state (GLONASS) and Chinese state (Baïdou). A European satellite constellation (Galileo) is in the process of being deployed. Generally, these navigation systems are designated by the acronym GNSS (Global Navigation Satellite Systems).
The basic principle behind satellite navigation and positioning is the calculation, using a receiver equipped with electronic processing circuits, position, velocity and time (PVT) data from electromagnetic signals of centimetre-scale wavelength emitted by satellites in orbit. The calculation of the PVT data by a receiver from signals from satellites is affected by many errors of various types: the impact of the passage by the electromagnetic signals through the various layers of the atmosphere (troposphere, ionosphere), errors due to reflection of the signals from objects in the vicinity of the receiver (multipaths), clock errors, errors in the electronic processing circuits, etc. For military applications, these errors are notably corrected using specialized signals emitted on reserved carriers (P(Y) code for GPS). Specific multi-sensor processing and combining means are furthermore generally provided in order to guarantee the precision and integrity of measurements intended for critical uses. However these solutions are restricted and expensive. To meet the growing need for precision in civil applications, various means have been developed to correct the main errors: acquisition of signals originating from a plurality of constellations; improvement of antennae in order to increase reception robustness; use of correlation loops in receivers; differential GPS, which calls upon fixed base stations that broadcast a reference signal allowing errors to be corrected; terrestrial networks for broadcasting correction information; combination of satellite data with data from movement sensors integrated into the receiver, or providing information on the path of the receiver (map, terrain models); etc. In parallel, for specific applications having a high need for integrity, such as aerial navigation, procedures have been developed for determining a radius of protection allowing a zone of safety in which the navigation solution is guaranteed to be valid to be determined.
There are thus various techniques of obtaining a precise position (or PPP for Precision Position Point). These techniques are based on the acquisition of GPS signals and on the acquisition of signals from other constellations. Certain thereof use signals from bi-frequency (EP2140285) and even tri-frequency (EP2335085) receivers. A non-built-up environment on a very clear day is often considered to be an ideal case as regards implementation of these techniques. In the case of actual use, buildings, trees, and other elements of the environment will greatly degrade the reception and processing conditions of the positioning signals. Therefore, the measurements will be less good, to the point of causing the signal to be lost. Furthermore, the choice of a GNSS receiver is often made depending on a compromise between technical performance, cost and need. For example, in an urban environment, with many multipaths, commercial sub-metre positioning solutions combine the acquisition of GPS signals, the acquisition of EGNOS signals, inertial sensors, a map, a terrain model, etc. If the need is for a precision of about ten metres, at the present time simpler GPS techniques are sufficient and the navigation software will possibly position the receiver “at best”.
For certain applications, it is not only necessary for the receiver to deliver a precise position/navigation measurement, but above all for it to give an indication of confidence in the measurement. Specifically, by way of nonlimiting example, for an autonomous vehicle driving on a road used by other traffic it is essential to be able to guarantee a measurement accurate to within one centimetre. It is also indispensable to be able to inform the driver of a foreseeable short-term degradation in the confidence of the position measurement so that he can retake control of the vehicle.
In aerial navigation, a radius of protection is defined around the aeroplane into which obstacles of the relief must not penetrate, but this radius of protection does not vary as a function of the conditions of reception of the navigation signals. Moreover, to take an example of a mass-market localization receiver, the “Maps” function of an iPhone™ indeed delivers an indication of the precision of the localization measurement under given reception conditions, this indication taking the form of a circle of a radius that varies depending on these conditions (large circle in the case of poor conditions; small circle in the case of good conditions). However, these indications are not proportional to the precision as regards distance, except when the localization is based on triangulation from Wi-Fi signals.
Thus, no prior-art system allows, at the present time, a measurement precision to be determined for the current and future position of a receiver of navigation signals depending on the hardware and software configuration of the receiver and its current position, so as to adapt, if needs be, the processing of the signals to obtain a given precision. It is particularly important to meet this need at a time when the Galileo constellation will soon become available, notably because the latter will permit for the first time civil receivers to acquire signals modulated at different frequencies. Specifically, the Applicant has observed experimentally that bi-frequency signals may deliver a lower precision, in certain environments, notably in the presence of multipaths, than the precision delivered by mono-frequency signals. It is therefore very useful to be able to adapt the way in which the positioning signals are processed depending on the operating conditions under which the receiver is being used.